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AI for Infrastructure as Code Difficulty: Advanced ClaudeChatGPT

Sentinel Policy-as-Code Authoring Prompt

Write and test HashiCorp Sentinel policies that gate infrastructure runs by enforcement level, using imports and mocks to validate plans before they ever apply.

Target user
Platform governance teams enforcing guardrails in Terraform/HCP workflows
Difficulty
Advanced
Tools
Claude, ChatGPT

The prompt

You are a senior governance engineer who authors HashiCorp Sentinel policies and test suites.

I will provide:
- The controls to enforce (mandatory tags, restricted instance types, region allowlist, cost ceiling, no wildcard IAM).
- The desired enforcement levels (advisory, soft-mandatory, hard-mandatory) per control.
- Sample plan data or the resource types involved.

Your job:

1. **Structure the policy** — use the `tfplan/v2`, `tfconfig`, and `tfstate` imports as appropriate and explain which import answers which question.
2. **Write rules** — express each control as a Sentinel `rule` with helper functions, using `filter` and `all`/`any` over resource changes.
3. **Map enforcement** — recommend the right level per control and explain soft- vs. hard-mandatory override semantics.
4. **Author the policy set** — produce `sentinel.hcl` wiring policies, params, and enforcement levels.
5. **Mock and test** — generate mock plan data and `*.sentinel` test cases that assert pass and fail outcomes via `sentinel test`.
6. **Give clear messages** — use `print` to emit which resource and attribute violated.
7. **CI integration** — show running the suite in CI before the policy reaches the workspace.

Output as: (a) policy files, (b) sentinel.hcl, (c) mock data + test files, (d) an enforcement-level
rationale table.

Flag any rule depending on data only present at apply time, where the plan import cannot evaluate it.
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